Robotics process automation, or RPA, is revolutionizing insurance operations. It’s drastically changing the way insurers operate; it’s the fastest-moving technology in the field today.
RPA in insurance isn’t without flaws, impacting millions of jobs across all carrier types. As new jobs will be created as large-scale RPA bots are implemented, insurance companies will need to find the balance between robotics and up-skilling existing employees to manage their own robots. In this article about how RPA will affect insurance, we will define what RPA in insurance is, how and why it is used, the risks involved, and how to scale process standardization to ensure a successful large-scale RPA implementation.
What Is Robotic Process Automation (RPA) in Insurance?
In insurance, RPA is defined as implementing software robots, from UiPath, Automation Anywhere, or Blue Prism, that are custom configured for each computer, without the use of code. These software robots assist in processing insurance work that is monotonous and repetitive, such as data transcribing from one system to another and automatic moving of PDF attachments from emails to core systems. With RPA, you’ll have an AI (artificially intelligent) workforce, a.k.a. robotic assistants, that take over basic computer commands to make “low-value add” high-repetition tasks less intensive on employees.
Insurance robots operate similarly to Excel macros. But unlike Excel macros, RPA bots can span multiple systems instead of being confined to just one. These robots work at the individual-data-field level across all core insurance systems and desktop applications employees the support data processing and communication. RPA processes actions down to the mouse click and keyboard entry level. Once they’re set up properly (more on that in a minute), they can do everything from opening applications to clicking, copying, and pasting information from one application to another, sending emails, and similar activities.
For established insurance providers, operations have traditionally (and heavily) relied on outdated legacy systems with limited connectivity to other applications—and lots of work done in Excel, manually (by highly-paid knowledge workers), outside of the systems to reconcile and transcribe data. Historically, this has resulted in an impassably-high hurdle for streamlining existing technologies, without a wholesale (and costly) reinvention of the entire company’s IT infrastructure.
For newer insurance companies, the stakes are lower for needing to implement RPA. They face fewer challenges when standing up systems, given their ability to leverage more modern and largely interconnected infrastructure from the get-go. Contrast their situation to that of well-established insurance providers, and you can see that it gets expensive to implement core systems that routinely fall short on the promises of automation.
This is why insurance companies—especially the established ones—are so excited about RPA. It finally lets them “connect the last mile” of their legacy insurance systems in a way that improves the customer experience and back-office efficiency – without new core technology that takes years to implement. Little wonder that RPA is changing the way insurance companies conduct business operations.
Top Six Benefits and Advantage of RPA in The Insurance Industry
Robots can help you link disparate legacy systems to conduct insurance operations faster, reduce labor costs, expedite new business onboarding, underwriting, customer service, and claims processes… all at the same time. With the shifting demographics of customers, customer interaction preferences are moving towards the digital and speed of transaction. Customers today expect consistent service levels and convenience while working with their insurance company – the same ease of service and cycle time that they might experience shopping online or while using online banking.
The only way your insurance company can tap the maximum benefits of RPA in an insurance use-case is by first standardizing as much of the manual work as possible. Deep, front-line process analysis and desk-level work standardization across the entire organization are, simply, essential for RPA. They’re what makes RPA in insurance worth the investment and the only way to build a business case.
As we’ve noted, the benefits from RPA in insurance can be both financial and operational in nature, improving back-office processes and the customer experience while saving money on labor. Basically, robotic process automation lets you do a lot more with what you have, or less.
When compared to traditional automation, robotic process automation in insurance has specific benefits, including:
- Increased Speed of Processing Insurance Claims – Claims processing requires adjusters to gather information from multiple documents to pass that information into various systems – time and time again. RPA can reduce this in less than 4 weeks.
- Reduced Policy Cancellation “after call work” – The cancelling of insurance policies is already a losing proposition. Excessive data transcribing during offboarding of customers can take up to 40% of policy holder services staff time – RPA can cut this in half.
- Support with Scaling with Growth – Sometimes insurance companies grow faster than the volume of claims that they are capable of processing. Robots can grow with the company as you can simply increase the number of robots to meet the demands of the companies’ growth.
- Improved Data Accuracy – Using insurance robotics increases the reliability of information because the robots will not have the human ability to key in the wrong information or have their mind wonder while doing repetitive tasks.
- Standardization of Processes – A side effect of analyzing processes to implement robots is the deep dive standardization of front line work. In order to start using robots, company process all need to be standardized, which in turn increases efficiency of workers and then greatly increases the speed at which the robots can do their work as well.
- Working with Legacy Systems – Robots can be configured to use old systems that could be replaced in the next few years. RPA does not require changes to underlying infrastructure.
What Are RPA Insurance Use Cases?
A Robotic Process Automation use case in the insurance industry is defined as the process of documenting a list of insurance operations steps that take place on the front-line employee level in preparation for robot installation. These documented actions and steps that are processed on computers or other electronic devices are then used to map requirements to automate information movement across the insurance applications. Insurance RPA use cases are utilized by IT consultants, or your own staff, as “blue prints” to implement automated actions that run across multiple systems to process data.
That may sound complicated, but it’s not. The 3-step process is detailed below:
Step 1: You must identify sub-processes on process maps where banking robots can be implemented.
Step 2: You must prioritize and evaluate all of the insurance sub-processes and use cases to see which yield the most benefits with the least amount of business impact and risk.
Step 3: Finally, develop the use-case requirements, rules and key strokes that the insurance robot must take over.
Six Examples of Robotic Process Automation Use-Cases in Insurance Companies Using RPA
Given this new robotic insurance frontier and legacy ways of doing business—most insurance companies struggle to find places to get started with RPA. Studying use-cases can help. They’ll give you new ideas of where you can install your insurance robots first. Consider these six examples of RPA insurance use-cases. Let them jump start the ideation for your robotics project:
- Insurance underwriting RPA use-case example.At one company, underwriting processing time was slashed by 80 percent—thanks to the elimination of manual copying and pasting of client information from inbound customer emails into one cloud-based underwriting system and two on-premises core insurance systems.
- Insurance quoting RPA use-case example.One insurance company used RPA to turbocharge policy-quoting speed by automatically copying contact data from requests on the company website and validating it on government websites such as DMV and third-party databases like as SambaSafety.
- P&C insurance claims analytics and reporting RPA use-case example: Another insurer increased the speed of its analytics insights by automatically moving automotive claims transaction volume data into its business-intelligence application… without human wrangling or intervention! Monthly report generation cycle time was reduced by 3 days.
- Life insurance claims RPA use-case example. A life insurance company slashed the cycle time of life insurance claims processing by 40 percent. They were able to automate what had been the manual entry of claims data by letting the bots validate death certificates on government websites.
- Insurance premium accounting RPA use-case example.Another insurer reduced home-office error correction by 50 percent for payments set up at agencies. How? They were able to automatically copy and move information from the new policy payment into the core insurance system, removing manual transcription of data by agencies.
- Life insurance in-force customer service RPA use-case example.One life insurance company reduced the overhead of customer service by 25 percent by automatically transcribing data from emailed policy-change requests into core systems.
In-Depth Insurance Claims RPA Use-Case Example
In this example of a robotic automation use case in insurance, “Cathy” processes insurance claims through the company’s numerous systems. Each claim takes 20 to 40 minutes to process. She normally has a queue, or backlog, of pending claims. This queue is the reason a customer claim can take several days to process and why it takes so long for policyholders to receive their money after an insurance claim.
The pre-RPA insurance use case process is as follows:
- Cathy receives an email with a new claim. Each claim form—a PDF—includes a new claim number. Her Outlook is set up to find these emails and send them automatically to a dedicated claims folder.
- She transfers each claim form into a queue folder on a shared network drive to be processed in order of receipt. This generates a backlog of 10 to 20 claims, or more.
- Cathy opens the oldest claim in the queue. First, she copies the account number from the form into the company’s system and finds the policyholder’s account.
- Then she opens the company’s insurance claims program and compares the information in the claim and policyholder’s account to make sure everything matches.
- She tediously copies the policyholder’s name, date of birth, social security number, address, claim number, account number and any other required information into the claims system. Then she attaches the PDF to the claim in the claims system.
- She moves the PDF from the queue folder to the finished folder. She then emails the claim payment processing department, notifying them that this claim is complete and ready to be paid.
- Cathy processes a few more claims before she breaks for lunch. When she returns, 10 more claims have arrived in her email. Consequently, Cathy never catches up; the queue continues to grow, causing a bottleneck in the claims process.
This whole process is done manually. And all of that manual processing reduces productivity and increases avoidable costs because the company’s claims processors are devoted to mind-numbingly repetitive tasks rather than making better use of their skills.
Now let’s look at the same process using robotics and see the difference in productivity. The post-RPA insurance use case processes the work as follows:
- Cathy receives the claim email, just as before. This time, however, she opens all the relevant systems and runs the robot.
- UiPath searches Cathy’s claims folder in Outlook. It finds the new email and saves the attachment to the network drive folder.
- UiPath opens the oldest claim in the queue, searches for policyholder’s account in the company’s system and compares the information. If it finds any discrepancies between the claim information and the account, the robot stops and saves the claim to a new folder called “Needs Review.” Cathy can concentrate her efforts on these “exceptions.”
- Because this robot runs on a loop, it continues to the next claim. If the information in that claim matches the account information in the system, the robot copies all of the claim information into the claims system and attaches the PDF.
- Next, UiPath uses a prebuilt (template) email to send the claim to the claim payment processing department, notifying them that it is complete and ready to be paid.
- Cathy goes to lunch but leaves the robot running.
- When she returns, the robot has finished processing claims. It received, saved and processed all 10 new claims that arrived while she was out.
- After lunch, Cathy opens the “Needs Review” folder to fix any discrepancies between these claims and the associated accounts.
Each of the claims that previously took Cathy 20 to 40 minutes now takes the robot only 4 minutes. Because the robot works continuously until all claims are processed, the queue is finished within about an hour. Also note that the robot processed claims while no one was being paid to do the work.
UiPath eliminated the bottleneck, removed repetitious, manual work and accelerated claims processing. Policyholders consequently receive their much-needed claim payment faster.
This sounds like something that you might want to try out, right?
RPA in Insurance Case Study: Robotic Process Automation in Insurance Claims Processing
To illustrate robotics in the insurance industry at work for an auto insurance company, we’re going to walk you through a robotics in insurance claims case study. Let’s call it “A day in the life of Dan, an auto insurance claims processor.”
Today, much of Dan’s work day is spent copying and pasting claims-form data from PDF files into a web-based data-management system. Dan must retrieve the PDF claims file from an email, then copy-and-paste all fields from the PDF into the doc-management system – 40 times per day. Once this is done, Dan next must create a new document and import all of the information from an invoice into it—and then attach it to the management system. Finally, Dan sends this to management for approval.
Not too bad, right? Dan is a good employee who does good work. But, with a robot at his side, Dan can be better. Much better.
Let’s replay the scene, but with the UiPath RPA installed.
Now, the RPA software logs into Dan’s email app and retrieve the PDF claims form. The bot navigates through different screens and actually controls Dan’s mouse and keyboard to copy-and-paste all of the individual fields of data from the PDF file into the doc-management system.
In this robotic process automation in insurance case study, the RPA insurance software then creates a new Word document, copies the information from an invoice, pastes it onto the new document, and attaches it to the document-management system. The insurance robot then sends the claim to the back office for approval. Just like that, Dan is now able to focus on more complex claims without the backlog of mundane copying and pasting that drain his time and energy.
Consider the before-and-after: Dan used to spend 15 minutes per claim on the above tasks. Now, with his robot running all the data-transcribing work, it only takes him 1 minute per claim. Just imagine the benefits of this robotic process automation in insurance use-case, once rolled out at large scale across the organization!
Robotic process automation in insurance claims: Standardize that work before you throw a robot at it!
The above use case examples are just several examples of many ways RPA is making insurance processes quicker and more cost-effective; saving the company money while boosting the customer experience. So how does the process of RPA implementation work? We’ve laid out a path, with key steps that must be completed when undertaking the jump into RPA on your own, or with the help of a professional.
While implementing RPA insurance claims processes may seem highly technical and difficult, it doesn’t have to be.
Ultimately, the right approach to standardizing work will help you immensely. Here, we’re going to review the five basic steps for conducting a simple RPA in insurance claims improvement analysis and implementation process. This will help you introduce RPA for all major processes without breaking the bank or exhausting programmer/developer manpower.
Step 1: Scope the RPA in insurance implementation project
The most effective way to start an RPA insurance project is to first determine a manageable scope. Start small, then roll out at scale. Don’t swing for the fences with an enterprise-wide scope before piloting a test across a single business unit. No matter what anyone else says, starting huge with RPA never works.
Common divisions in insurance companies include: Agency Operations, Underwriting, New Business Processing, Policyholder Services, and Claims. We always suggest picking one division as your starting point: Claims. We love working in Claims because you can reduce overhead costs and reduce claims severity at the same time.
Claims departments are rife with multiple customer interactions, manual work, and usually revolve around anywhere from four to seven different systems and desktop applications that claims reps must toggle through as they move data every day. To begin, determine a group of 50 to 100 employees whom you know will be open to change. Start your process mapping exercise with them. A key part of building an insurance RPA scope is identifying which areas in your company are good candidates for RPA.
Remember, starting with too big of a scope will almost certainly set you up for quick failure. Start small. See how the organization responds. Learn your lessons about the cultural response to insurance RPA. Then scale up.
Step 2: Determine baseline insurance operations cost to calculate total benefits realized from RPA in insurance implementation
There is a wide range of financial benefits that can be reaped from insurance RPA use case implementation, so it is essential to know the baseline operational costs before attempting to add robots into your processes. It generally takes a week or two to get the numbers for your baseline operational costs, so be sure to budget that time into your plans. This will also require coordination with HR to get the cost for each employee in scope.
Don’t forget to measure the costs after the initial attempt of implementing RPA, as well as subsequent attempts. This data will allow you to show costs and savings achieved over a range of time due to RPA use. You want to have proof, and numbers don’t lie, that insurance RPA will deliver strong financial benefits before you implement it into every process.
Step 3: Analyze the current state of company processes to document opportunities for robotic process automation in insurance
This is the hard part, but also the most important – so be sure not to skip it! It’s time to deep dive into process mapping in your insurance processes. Each and every system and person that you’re considering adding RPA to will need to be fully mapped out. A thorough process analysis of all front and back office tasks needed to carry out operations is essential for determining how RPA can help. This isn’t just mapping at surface level either, it needs to be down to mouse click level.
One way to do this is conducting something called “day in the life of” observations that we do here at The Lab. These are carried out face-to-face or by screen sharing software. We watched workers perform tasks for a whole week, all day long, to document all areas where insurance RPA can be used. GoToMeeting, Webex or Team Viewer are our favorites for off-site observations.
After you’ve determined all the areas where RPA can be implemented, you’ll need a process mapping software such as Microsoft Visio to visually represent the steps to build your insurance RPA use cases. Every detail that goes into the workflow (down to mouse clicks and keystrokes) must be represented. A good way to document this is by using BPMN 2.0 stencil, a “coding level standard” way of representing process flows. This allows an easy handoff to the IT department of RPA vendor. This process will need to be completed for each employee until you have a large enough sample size to verify your findings. It might not be easy but remember that the payoff is well worth the effort.
Time for the next step – standardizing insurance processes before robotic process automation implementation. If you’re not prepared to analyze and standardize your current manual processes, you shouldn’t be jumping into RPA. To successfully and efficiently roll out Insurance RPA to scale means that everything must first be thoroughly planned out and standardized.
Find project managers with lean project experience, they will serve your RPA insurance use cases well with their knowledge on transactional and white-collar process work.
Step 4: Standardize workflow and procedures before or during RPA in insurance implementation—but not after
Don’t even think about RPA in insurance claims if you aren’t ready to analyze and standardize manual processes first. This is the vital “brain food” that RPA bots require in order to do their jobs.
As we’d mentioned earlier, insurance processes vary greatly across different companies. But they also vary internally just as much. Employee A almost
never processes work in the same order as Employee B. The key to insurance companies using RPA successfully is standardizing everyone’s work processing similarly, so it can be rolled out to everyone the exact same way.
Project managers with lean and Six Sigma experience are the best candidates for creating RPA insurance use cases, based on their previous work experience with standardization of processes at scale.
Step 5: Hire an RPA consultant or vendor to implement insurance claims RPA —or do it yourself
RPA is easiest when you hire a vendor to show your insurance company the areas that RPA can improve upon. They can help you map flow charts and plan process standardization business cases—and they can then install the actual RPA in claims processing technology to put said plans into action. The cost of RPA analysis varies greatly by consulting firm, and big names will charge you millions. There are also smaller specialty shops that will gladly look at smaller groups for much less. Contact us if you want to implement insurance RPA with less cost and risk.
Feeling in a DIY mood? There are options for those who wish to take on RPA implementation with their own two hands. The Community Version of UiPath is free, and RPA certification courses can be completed in one month online. But if you have a large-scale project and you’re the one in charge, you’ll need Six Sigma training.
The risks of robotics and RPA in Insurance
New technology always comes with risks. However, when compared to the long term technology implementations, the operational risk of RPA is rather low. Since RPA is like a layer that runs in the background, shutting down a robot won’t harm your core insurance processes, if you choose to do so. Nor do robots require organization wide change management, they only affect individual user desktop setting. If your robots are only data transcribing and scraping, they won’t bring down your IT systems if something goes wrong.
Risk categories of RPA in banking include:
- Operational Risk
- Compliance Risk
- Data Quality Risk
- Ethical Risk
Everyone has probably heard something along the lines of “robots are going to steal your job!” in one way or another. Beginning any RPA project will probably come with a risk of push back from internal staff. Be sure to clearly communicate the goals of the project, letting staff know that the robot is simply a tool to help them reduce the amount of work required to move data. Aside from pushback from staff, operating system updates could also cause robot downtime. RPA robots will need to be updated and repaired from time to time, luckily robots can be updated within a few hours should they need to be reconfigured.
Project managers should always have an inventory of installed insurance robots, so that unchecked robots don’t become problematic. Robots that aren’t built to adhere to compliance processes can lead to massive issues within compliance. This is why insurance robots should only act as an extension of humans, not replacing them, unless it has been fully thought out. Insurance RPA is end user-friendly, but management of the technology requires discipline and decision making abilities.
Data Quality Risk
Robots certainly help to cut down in the amount of bad data in back-office transcribing operations, but not if the data is already in bad order when it’s received from the front office. A robot is transcribing 100x more data into the system and if that data is sent to the robot in bad quality – we’ve landed in quite a problematic situation with bad data flooding into the system. “Big data” standardization processes are an element that should never be overlooked during RPA implementation.
Ethics is in the forefront of a lot of conversations recently. Companies must balance investments into people and technology. If an enterprise only invests in technology and neglects their human workforce, moral will quickly plummet. Thankfully RPA combines humans and technology, allowing a balanced investment in your human workforce and technology while boosting profits and cutting costs.
Benefits of choosing The Lab for RPA insurance analysis, use-case development, and implementation
So, you’ve looked at your choices and have a solid plan for implementing RPA. Now what?
If your decision is “Hire someone to help,” we’re pleased to present a variety of solutions for robotics in insurance industry. Interested in using the power of RPA for your insurance company? Feel free to get in touch with us to learn more.